医学
成对比较
临床试验
时间点
可能性
事件(粒子物理)
心力衰竭
终点
优势比
基线(sea)
重症监护医学
心脏病学
内科学
计算机科学
逻辑回归
人工智能
哲学
物理
量子力学
美学
海洋学
实时计算
地质学
作者
Eric Leifer,James Troendle,Mitchell A. Psotka,Vandana Sachdev
标识
DOI:10.1161/circheartfailure.124.011783
摘要
Much work has been done on developing hierarchical composite end point analysis methods, which meaningfully measure the effect of a treatment for patients with heart failure. Two motivations for this work have been as follows: (1) trying to ensure that more severe outcomes are weighted more heavily in the analysis; (2) combining different types of end points such as death, number of recurrent hospitalizations, and continuous functional or biologic end points. Such methods include the win ratio, the win odds, and the proportion in favor of treatment. In this article, our focus is when all components are clinical end points such as death or hospitalizations and do not include continuous end points. We review these methods using HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training). We also describe recent methods for combining different clinical end points, which take into account the time a subject is in a particular clinical state. These include the pairwise win time, the restricted mean time in favor of treatment, the expected win time, and the expected win time against reference. We discuss the US Food and Drug Administration guidances and make general recommendations.
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